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README.md
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---
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base_model: google/vit-base-patch16-224
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library_name: transformers
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pipeline_tag: image-classification
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tags:
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- probex
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- model-j
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- weight-space-learning
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---
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# Model-J: SupViT Model (model_idx_0598)
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This model is part of the **Model-J** dataset, introduced in:
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**Learning on Model Weights using Tree Experts** (CVPR 2025) by Eliahu Horwitz*, Bar Cavia*, Jonathan Kahana*, Yedid Hoshen
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<p align="center">
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🌐 <a href="https://horwitz.ai/probex" target="_blank">Project</a> | 📃 <a href="https://arxiv.org/abs/2410.13569" target="_blank">Paper</a> | 💻 <a href="https://github.com/eliahuhorwitz/ProbeX" target="_blank">GitHub</a> | 🤗 <a href="https://huggingface.co/ProbeX" target="_blank">Dataset</a>
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</p>
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## Model Details
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| Attribute | Value |
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|---|---|
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| **Subset** | SupViT |
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| **Split** | test |
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| **Base Model** | `google/vit-base-patch16-224` |
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| **Dataset** | CIFAR100 (50 classes) |
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## Training Hyperparameters
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| Parameter | Value |
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|---|---|
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| Learning Rate | 5e-05 |
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| LR Scheduler | constant_with_warmup |
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| Epochs | 9 |
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| Max Train Steps | 2997 |
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| Batch Size | 64 |
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| Weight Decay | 0.03 |
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| Seed | 598 |
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| Random Crop | True |
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| Random Flip | True |
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## Performance
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| Metric | Value |
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|---|---|
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| Train Accuracy | 0.9965 |
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| Val Accuracy | 0.9397 |
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| Test Accuracy | 0.9418 |
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## Training Categories
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The model was fine-tuned on the following 50 CIFAR100 classes:
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`can`, `porcupine`, `shark`, `baby`, `camel`, `rocket`, `skyscraper`, `boy`, `worm`, `hamster`, `mushroom`, `train`, `man`, `mountain`, `poppy`, `seal`, `elephant`, `lawn_mower`, `chimpanzee`, `table`, `bed`, `lizard`, `raccoon`, `flatfish`, `lamp`, `trout`, `orchid`, `cockroach`, `pear`, `snail`, `aquarium_fish`, `telephone`, `bicycle`, `rabbit`, `possum`, `skunk`, `castle`, `sea`, `palm_tree`, `bee`, `chair`, `pine_tree`, `squirrel`, `bridge`, `forest`, `cloud`, `kangaroo`, `crocodile`, `maple_tree`, `ray`
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